This paper presents the Cervical Kinematic Recorder (CKR) application, a tool designed to replicate and capture cervical movements performed in a clinical setting using a virtual reality environment. By extracting accelerometer signals, we developed a classification model capable of accurately distinguishing healthy individuals from patients with left or right cervical dysfunctions. The study also demonstrates how signal-processing features of Yaw, Pitch, and Roll can be used to characterize these patient categories, providing interpretable insights into the kinematic patterns associated with cervical impairments. This approach offers a promising avenue for objective assessment and monitoring of cervical function in clinical practice.